A New Topology for Tumour and Edema Segmentation Using Artificial Neural Network

Brain magnetic resonance (MR) segmentation algorithms are critical to analyze tissues and diagnose edema and tumor in a quantitative way. The primary aim of brain image segmentation is to partition a given brain image into different regions representing anatomical structures. In this paper, we present a new effective segmentation algorithm that segments brain MR images into tumor, edema, white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The detection of the healthy tissues and the diseased tissues are performed for examining the change caused by the spread of tumor and edema on healthy tissues is very important for treatment planning. We developed an algorithm for skull stripping before the segmentation process. The segmentation is performed using feed forward backpropogation algorithm.